Deep Learning for Enhanced Security in the Internet of Nano Things: A Study on Data Classification for Normal and Abnormal Behavior

The Internet of Nano Things (IoNT) is a new frontier in technology that has opened up vast possibilities in the field of internet connectivity. With the proliferation of nanoscale devices and the ability to network them, the potential for a more efficient and effective Internet of Things (IoT) has become a reality. However, increased connectivity has also raised security issues that need to be addressed. This research paper aims to provide a comprehensive review of the security challenges posed by the IoNT and proposes the use of Artificial Intelligence (AI) and Machine Learning (ML) techniques to detect and prevent cyber-attacks. The paper presents experimental and evaluative work on selected ML algorithms using a real-world dataset to demonstrate and analyze the effectiveness of ML in securing IoNT.